Data warehouse is a central repository to store data for an organization or an enterprise. The data warehouse integrates and stores the data acquired from one or more data sources. Often, the data warehousing project life cycle comprises different processes such as defining business requirements, generating code, reviewing the generated code, testing data and storing the data into the data warehouse. The data stored in the data warehouse is used for business intelligence and strategic decision making by the organization or the enterprise.
Conventionally, various systems and methods exist in the form of individual solutions that partially automate specific processes of the data warehousing project life cycle. Further, the individual solutions are provided by different vendors having specific versions. The organization or the enterprise has to opt for multiple individual solutions provided by different vendors having limited functionality and specific versions for data warehousing project life cycle. Moreover, the individual solutions provide partial automation and limited usability. The data warehousing project life cycle and its associated processes thus require considerable time and manual effort on part of the organization or the enterprise. Therefore, an integrated and comprehensive system and method for automating various data warehousing processes during data warehousing project life cycle does not exist.
In light of the above, there is a need for a system and method for automating one or more data warehousing processes during the data warehousing project life cycle. Further, there is a need for a system and method which is cost-effective and facilitates saving time and manual effort for the organization or the enterprise. Furthermore, there is a need for a system and method that is scalable and provides high level of performance. In addition, there is a need for a platform to integrate the multiple individual solutions provided by different vendors and having specific versions.